Authors:
Inês Rito Lima
1
;
Nuno V. Leite
1
;
Adriano Pinto
1
;
Pedro Pires
2
;
Carlos Martins
2
and
Nuno V. Lopes
1
Affiliations:
1
DTx Digital Transformation Colab, 4800-058, Guimarães, Portugal
;
2
Mobileum, 4705-319, Braga, Portugal
Keyword(s):
Automatic Machine Learning (AutoML), Explainable AI (XAI), General-purpose, Telecommunications, Anomaly and Fraud Detection.
Abstract:
The combination of high computational power and data awareness triggered an increasing demand for business applications from industrial players. However, harnessing the knowledge from data requires expertise, usually being a time-consuming task. Additionally, the users’ trust in the results obtained is commonly compromised due to the black box behavior of most Machine Learning models. This paper proposes a general-purpose platform, eSardine, that leverages automatic machine learning and explainability to produce fast, reliable, and interpretable results. The eSardine platform integrates forefront tools to enhance, and automate the data science process, with minimal human interaction. For any tabular supervised classification and regression problems, predicted outputs are given, as well as an explainability report of each prediction. The inclusion of AutoML tools, i.e. , automatic model tuning and selection, presented a strong baseline whose capabilities are amplified by built-in, yet
customizable, autonomous processing mechanisms. The explainable reports aim to increase users’ confidence in the models’ quality and robustness. Furthermore, in the industrial context, understanding key factors unveiled in these reports is determinant to increase the business model’s profitability. The platform was evaluated in two public datasets, where it outperformed state-of-the-art results.
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